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Measuring Asymmetry in Time-Stamped Phylogenies.

Dearlove BL, Frost SD - PLoS Comput. Biol. (2015)

Bottom Line: We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate.We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry.In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models.

View Article: PubMed Central - PubMed

Affiliation: Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Previous work has shown that asymmetry in viral phylogenies may be indicative of heterogeneity in transmission, for example due to acute HIV infection or the presence of 'core groups' with higher contact rates. Hence, evidence of asymmetry may provide clues to underlying population structure, even when direct information on, for example, stage of infection or contact rates, are missing. However, current tests of phylogenetic asymmetry (a) suffer from false positives when the tips of the phylogeny are sampled at different times and (b) only test for global asymmetry, and hence suffer from false negatives when asymmetry is localised to part of a phylogeny. We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate. We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry. In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models.

No MeSH data available.


Related in: MedlinePlus

Calculating local asymmetry.For each internal node of an observed tree (a) it is possible to calculate the node contribution and cumulative number of cherries (b) and Sackin’s index (c).
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pcbi.1004312.g001: Calculating local asymmetry.For each internal node of an observed tree (a) it is possible to calculate the node contribution and cumulative number of cherries (b) and Sackin’s index (c).

Mentions: There are two main types of event that can affect the shape of a phylogeny: a coalescence, and a new sampling event, which adds a tip. Sackin’s index and the number of cherries are both concerned with internal nodes rather than the tips, so we need only consider the former. At each coalescent event, we consider the contribution of that node to the overall metric. This results in a vector of n − 1 values, one for each ancestral node, giving a measure of how asymmetric the subtree below the node is (Fig 1). We can add these values cumulatively as we go backwards in time from the present towards the root, to investigate how asymmetry builds up over the course of the tree.


Measuring Asymmetry in Time-Stamped Phylogenies.

Dearlove BL, Frost SD - PLoS Comput. Biol. (2015)

Calculating local asymmetry.For each internal node of an observed tree (a) it is possible to calculate the node contribution and cumulative number of cherries (b) and Sackin’s index (c).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492995&req=5

pcbi.1004312.g001: Calculating local asymmetry.For each internal node of an observed tree (a) it is possible to calculate the node contribution and cumulative number of cherries (b) and Sackin’s index (c).
Mentions: There are two main types of event that can affect the shape of a phylogeny: a coalescence, and a new sampling event, which adds a tip. Sackin’s index and the number of cherries are both concerned with internal nodes rather than the tips, so we need only consider the former. At each coalescent event, we consider the contribution of that node to the overall metric. This results in a vector of n − 1 values, one for each ancestral node, giving a measure of how asymmetric the subtree below the node is (Fig 1). We can add these values cumulatively as we go backwards in time from the present towards the root, to investigate how asymmetry builds up over the course of the tree.

Bottom Line: We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate.We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry.In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models.

View Article: PubMed Central - PubMed

Affiliation: Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Previous work has shown that asymmetry in viral phylogenies may be indicative of heterogeneity in transmission, for example due to acute HIV infection or the presence of 'core groups' with higher contact rates. Hence, evidence of asymmetry may provide clues to underlying population structure, even when direct information on, for example, stage of infection or contact rates, are missing. However, current tests of phylogenetic asymmetry (a) suffer from false positives when the tips of the phylogeny are sampled at different times and (b) only test for global asymmetry, and hence suffer from false negatives when asymmetry is localised to part of a phylogeny. We present a simple permutation-based approach for testing for asymmetry in a phylogeny, where we compare the observed phylogeny with random phylogenies with the same sampling and coalescence times, to reduce the false positive rate. We also demonstrate how profiles of measures of asymmetry calculated over a range of evolutionary times in the phylogeny can be used to identify local asymmetry. In combination with different metrics of asymmetry, this combined approach offers detailed insights of how phylogenies reconstructed from real viral datasets may deviate from the simplistic assumptions of commonly used coalescent and birth-death process models.

No MeSH data available.


Related in: MedlinePlus